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6 дней назад

Senior Solutions Architect (Databricks)

Формат работы
remote (только Brazil)
Тип работы
project
Грейд
senior
Английский
b2
Страна
Brazil
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Senior Solutions Architect (Databricks): Designing and implementing production-grade big data solutions for strategic enterprise customers with an accent on Apache Spark, Databricks, data engineering, and cloud architecture. Focus on optimizing end-to-end data pipelines, guiding model deployment, solving complex performance challenges, and presenting technical strategies to senior stakeholders.

Location: Remote from Brazil, with significant time zone overlap with clients; rare exceptions may be agreed upon.

Company

Provides data warehouses, business intelligence, data analytics, application development, and other business technology solutions for Hungarian and international customers.

What you will do

  • Provide post-sales technical leadership for strategic customers building large-scale big data projects.
  • Design architectures spanning data engineering, production workloads, and model deployment.
  • Lead performance testing and optimization of end-to-end data pipeline loads.
  • Align technical roadmaps with customer business goals and identify initiatives that create measurable data value.
  • Deliver tutorials, training sessions, hackathons, and conference presentations to support community adoption.

Requirements

  • Hands-on expertise with Apache Spark and Databricks across several large-scale projects.
  • Databricks Certified Data Engineer Professional certification.
  • More than 5 years of software or data engineering experience, including query tuning, performance tuning, troubleshooting, and debugging.
  • Experience with Hadoop, NoSQL, MPP, OLTP, OLAP, cloud services, and programming in Python, Scala, or Java.
  • Familiarity with CI/CD, testing, automation, orchestration, REST APIs, BI tools, and SQL interfaces.
  • Advanced English and significant client time zone overlap are required.

Nice to have

  • Data science or ML engineering experience, including model selection, lifecycle management, hyperparameter tuning, model serving, deep learning, and MLflow.
  • Customer-facing experience in pre-sales, post-sales, technical architecture guidance, or consulting.

Culture & Benefits

  • Flexible ways of working with autonomy over when and how work is performed.
  • Mentoring and continuous support from the first day.
  • Learning and development opportunities through training and career support.
  • Diverse technical and business projects with opportunities for professional growth.
  • Supportive, respectful culture focused on collaboration and work-life balance.

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